A precise sensor fault detection technique using statistical techniques for wireless body area networks

One of the major challenges in wireless body area networks (WBANs) is sensor fault detection. This paper reports a method for the precise identification of faulty sensors, which should help users identify true medical conditions and reduce the rate of false alarms, thereby improving the quality of services offered by WBANs. The proposed sensor fault detection (SFD) algorithm is based on Pearson correlation coefficients and simple statistical methods. The proposed method identifies strongly correlated parameters using Pearson correlation coefficients, and the proposed SFD algorithm detects faulty sensors. We validated the proposed SFD algorithm using two datasets from the Multiparameter Intelligent Monitoring in Intensive Care database and compared the results to those of existing methods. The time complexity of the proposed algorithm was also compared to that of existing methods. The proposed algorithm achieved high detection rates and low false alarm rates with accuracies of 97.23% and 93.99% for Dataset 1 and Dataset 2, respectively.     

Characterization of anisotropic gas permeability and thermomechanical properties of highly textured porous alumina

Porous alumina with a highly textured microstructure was fabricated by pulse electric current sintering (PECS) using alumina platelets. Highly oriented porous alumina with a porosity of 3%–50% was obtained by a pressure-controlled method of PECS. The properties of the highly textured porous alumina were measured in two directions. The nitrogen gas permeance and thermal conductivity at room temperature were higher in the direction along the platelet length due to the higher continuity of pores and the connectivity of alumina platelets, respectively. The anisotropy of the thermal conductivity at room temperature was investigated and explained by the effect of grain size of platelets as well as morphology and orientation of pores. The bending strength was higher with the loading direction along the platelet thickness. The thermal shock strength was clearly different in the two directions. The difference in the thermal shock strength was investigated by the measurement of properties and thermal stress analysis.     

Omega-6支撑身体，Omega-3支撑大脑：均衡摄入对儿童大脑发育的影响（网络首发、推荐阅读）

人体大脑和身体的发育，需要从食物中摄取均衡的营养物质。人类大脑是区分人类和其他动物的特征。食物中的必需脂肪酸是机体组织结构和功能的必要组成部分。Omega-6（O6）亚油酸（LA6）是皮肤组织的组成成分，且是炎症、血栓形成、免疫和其他信号分子的前体；Omega-3（O3）α-亚麻酸（ALA3），特别是其长链代谢产物——二十二碳六烯酸（DHA3），是大脑、视网膜和部分神经组织中的关键组分。从富含LA6脂肪酸（缺乏O3脂肪酸）的植物籽中提取出的廉价而优质油脂，是20世纪的西方国家食品工业生产的主要脂肪来源。在代谢通路中，高浓度的LA6脂肪酸可拮抗O3脂肪酸代谢，造成O3脂肪酸不足，因此，在给怀孕动物的饲料中，只提供富含LA6但缺乏O3脂肪酸的油脂作为唯一的脂肪来源，会导致幼崽大脑发育不良。过去20~30年的研究表明，低含量LA6且含DHA3的油脂可改善大脑的功能。近年来的研究较多集中在营养因素对大脑发育的影响，最新研究数据表明，脂肪酸平衡对营养不良儿童的大脑发育尤为重要。世界卫生组织（WHO）越来越重视大脑的营养健康，通过其下属的食品法典委员会，建议用于治疗严重急性营养不良儿童的即食治疗食品中，使用含有均衡脂肪酸组成/构成的脂肪。同样，脂肪酸均衡对老年人可能也很重要。目前，业界已经有了调整油脂成分的方法，以确保脂肪酸均衡，从而维持人体整个生命周期的大脑健康。     

高效液相色谱法测定多环芳烃的出峰顺序探讨

目的探讨水﹑气﹑土壤中多环芳烃检测标准(HJ 478-2009﹑HJ 647-2013、HJ 784-2016)的正确出峰时间和顺序。方法用高效液相色谱来对苊烯、芴、苊、?、苯并(a)蒽进行定性分析,并与3个标准中的出峰顺序进行比较。结果苊烯、苊、芴、苯并(a)蒽、?的出峰时间分别为6.450、7.923、8.233、17.760、18.740min,与标准HJ478-2009﹑HJ647-2013的出峰顺序存在差异。结论在使用标准HJ478-2009﹑HJ647-2013、HJ 784-2016同时测定16种多环芳烃时,多环芳烃的出峰顺序及时间应以HJ 784-2016为准。     

A single-phase algorithm for mining high utility itemsets using compressed tree structures

Mining high utility itemsets (HUIs) from transaction databases considers such factors as the unit profit and quantity of purchased items. Two-phase tree-based algorithms transform a database into compressed tree structures and generate candidate patterns through a recursive pattern-growth procedure. This procedure requires a lot of memory and time to construct conditional pattern trees. To address this issue, this study employs two compressed tree structures, namely, Utility Count Tree and String Utility Tree, to enumerate valid patterns and thus promote fast utility computation. Furthermore, the study presents an algorithm called single-phase utility computation (SPUC) that leverages these two tree structures to mine HUIs in a single phase by incorporating novel pruning strategies. Experiments conducted on both real and synthetic datasets demonstrate the superior performance of SPUC compared with IHUP, UP-Growth, and UP-Growth+ algorithms.     

Cyclic thermal shock resistance of h-BN composite ceramics with La2O3–Al2O3–SiO2 addition

The effects of La₂O₃–Al₂O₃–SiO₂ addition on the thermal conductivity, coefficient of thermal expansion (CTE), Young's modulus and cyclic thermal shock resistance of hot-pressed h-BN composite ceramics were investigated. The samples were heated to 1000 °C and then quenched to room temperature with 1–50 cycles, and the residual flexural strength was used to evaluate cyclic thermal shock resistance. h-BN composite ceramics containing 10 vol% La₂O₃–Al₂O₃ and 20 vol% SiO₂ addition exhibited the highest flexural strength, thermal conductivity and relatively low CTE, which were beneficial to the excellent thermal shock resistance. In addition, the viscous amorphous phase of ternary La₂O₃–Al₂O₃–SiO₂ system could accommodate and relax thermal stress contributing to the high thermal shock resistance. Therefore, the residual flexural strength still maintained the value of 234.3 MPa (86.9% of initial strength) after 50 cycles of thermal shock.     

Improved Corrosion Resistance of Selective Laser Melted Ti–5Cu Alloy Using Atomized Ti–5Cu Powder

The different types of metal powder used for selective laser melting(SLM) process would cause distinct corrosion behavior due to the uniformity of the obtained microstructure.The SLM-produced Ti–5Cu alloy using atomized Ti–5Cu metal powder(SLMed Ti–5Cu) in this work reveals a relatively uniform microstructure with overwhelming acicular α/α′ phase and shows great advantages on corrosion resistance compared with the SLM-produced Ti–5Cu alloy using the mixture powder(SLMedM Ti–5Cu).The effect of the micro-galvanic cells decreases due to the undetectable Ti_2Cu phase in the microstructure of the SLMed Ti–5Cu.An apparent passivation behavior was observed for SLMed Ti–5Cu instead of severe pitting phenomenon for the SLMed-M Ti–5Cu.The charge transfer resistance of SLMed Ti–5Cu in this work is 10.09 ± 2.63 MΩ cm~2, which is significantly higher than that of SLMed-M Ti–5Cu(4.76 MΩ cm~2).The above result indicates the atomized Ti–5Cu powder plays an important role in the formation of the uniform microstructure of SLMed product, thereby enhancing its corrosion resistance in Hank's solution at 37 ℃.     

ACCUGRAM: A novel approach based on classification to frequency band selection for rotating machinery fault diagnosis

Frequency band selection (FBS) in rotating machinery fault diagnosis aims to recognize frequency band location including a fault transient out of a full band spectrum, and thus fault diagnosis can suppress noise influence from other frequency components. Impulsiveness and cyclostationarity have been recently recognized as two distinctive signatures of a transient. Thus, many studies have focused on developing quantification metrics of the two signatures and using them as indicators to guide FBS. However, most previous studies almost ignore another aspect of FBS, i.e. health reference, which significantly affect FBS performance. To address this issue, this paper investigates importance of a health reference and recognize it as the third critical aspect in FBS. With help of the health reference, the frequency band where the fault transient exists could be located. A novel approach based on classification is proposed to integrate all three aspects (impulsiveness, cyclostationarity, and health reference) for FBS. Classification accuracy is developed as a novel indicator to select the most sensitive frequency band for rotating machinery fault diagnosis. The proposed method (coined by accugram) has been validated on benchmark and experiment datasets. Comparison results show its effectiveness and robustness over conventional envelope analysis, the kurtogram, and the infogram.